Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis
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University of Cincinnati / OhioLINK
2018
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523630352322552 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin15236303523225522021-08-03T07:06:04Z Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis Kalagotla, Dilip Aerospace Materials Numerical modeling Multiphase analysis PIV SBLI Validation techniques Particle drag modeling Since its inception, Particle Image Velocimetry (PIV) has been increasingly used to measure the velocity of the flow field, especially in aerospace applications. One of the major assumptions of PIV is that velocity of the flow field is same as the velocity of tracers in it. The ability of PIV to measure velocity depends upon the potential of tracers to track the flow surrounding them.Shock-Boundary Layer Interactions (SBLIs) have been studied extensively over the years using experimental and computational methods due to their importance in almost every supersonic flow. PIV has been doing a great job in analyzing SBLIs over the past few years but it has its limitations especially when there are high temporal and spatial accelerations. On the other hand, numerical simulations that better predict shock interactions have a hard time analyzing the turbulence properties of SBLIs. This implies that only by using both computational and experimental results together physics of SBLIs can be better understood.The current study was divided into two parts. First, development and validation of a post-processing code to be able to accommodate the solid particles. For this, Visual3 has been chosen because it lets a user control even smallest of its processes. Visual3 code has been modified to track particles using accurate physics within a flow. Forces acting on a particle in a flow were analyzed and compared using data obtained from Modified-Visual3 (MV3). Based on this data, dominant forces on a particle in high-speed flow are determined. Results obtained from Modified-Visual3 are compared with Melling(1997) data to validate the code. A specific case is solved mathematically to compare with Modified-Visual3 and Melling's data. A second validation was done using an example of a generalized oblique shock to understand the behavior of the particle passing through the shock. Finally, particle relaxation times for different particle specifications were calculated to understand which particles have better traceability to use in Particle Image Velocimetry(PIV).Second, the MV3 code was used to post-process the CFD results of the UM-PIV data. These CFD results were obtained from the numerical analyses conducted at the UC. A standard case with 2.75 Mach and 7.75° wedge angle were used in MV3 to be in compliance with the CFD analysis. Particle, fluid velocities, position at every instant were collected from MV3 and were later used for comparison. This obtained data was filtered using a Python script to compare with the experimental plane defined in Eagle's (2011) work. Different particle sizes were used to compare the obtained results. These results were then used to analyze particle lag, velocity differences, velocity and acceleration contours. Finally, an error analysis was done to compare PIV, CFD and particle data.Results obtained from particulate data showed remarkable improvement in agreement with experimental data. Streamwise velocity, which was previously a major drawback, has shown a considerable improvement. This implies that particle lag in PIV plays an important role in analyzing flow especially when there are high spatial accelerations as is the case in SBLIs. 2018-07-24 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523630352322552 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523630352322552 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
| collection |
NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Aerospace Materials Numerical modeling Multiphase analysis PIV SBLI Validation techniques Particle drag modeling |
| spellingShingle |
Aerospace Materials Numerical modeling Multiphase analysis PIV SBLI Validation techniques Particle drag modeling Kalagotla, Dilip Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| author |
Kalagotla, Dilip |
| author_facet |
Kalagotla, Dilip |
| author_sort |
Kalagotla, Dilip |
| title |
Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| title_short |
Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| title_full |
Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| title_fullStr |
Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| title_full_unstemmed |
Modeling Particle Drag in Accelerating Flows with Implications for SBLI in PIV - A Numerical Analysis |
| title_sort |
modeling particle drag in accelerating flows with implications for sbli in piv - a numerical analysis |
| publisher |
University of Cincinnati / OhioLINK |
| publishDate |
2018 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1523630352322552 |
| work_keys_str_mv |
AT kalagotladilip modelingparticledraginacceleratingflowswithimplicationsforsbliinpivanumericalanalysis |
| _version_ |
1719453802580410368 |